Many people utilize computer-based mapping applications to obtain various types of information for a location. For example, users often rely on these the computer-based mapping applications to provide them with directions to a location, locate places near a current or specific location, or search for businesses or points of interest. Label rendering engines are responsible for rendering the labels associated with this information on the map. These labels can include street names, airport names, park names, zip codes, highways, city names, and the like. The label rendering engines are optimized to avoid collisions between labels, reduce busyness or clutter, and display appropriate labels for a particularly displayed geometry, such as a point for a coffee shop, polygon for a park and the like. The quality of the label rendering depends at least in part on the underlying data and collision algorithms. The label data or the associated geometry is updated regularly to reflect changes in the real world entities, such as businesses or points of interest, such as if a coffee shop moves from one address to another, or if a park or street is renamed, a new building is built, a city block is rezoned, and the like. These data changes or changes in the rendering algorithms can reflect poorly on the perceived quality of the mapping application product by the consumer if they are not adequately or properly presented to the same, such as if a user drives to a now closed coffee shop or seeing corn field labeled as an airport. Traditionally these data changes are manually validated for quality. While this is effective for identifying obvious errors, it is quite difficult to manually visit every single location in the world maps at each magnification or zoom level to verify that each rendering engine has properly rendered each label and map feature as these maps are constantly being changed.